Yalin Zhou
Papers
1
Total Citations
8
H-Index
1
About
Yalin Zhou is a robotics researcher specializing in autonomous manipulation and intelligent manufacturing, with a focus on contact-rich tasks that demand high precision and safety. His most cited work, "Robotic Manipulation Planning for Automatic Peeling of Glass Substrate Based on Online Learning Model Predictive Path Integral" (2022, 8 citations), addresses a critical challenge in LCD panel production: the automatic peeling of fragile glass substrates. Zhou’s key contribution lies in integrating online learning with model predictive path integral control to enable robots to adaptively plan and execute delicate, contact-rich manipulations—tasks traditionally reliant on human skill. This work demonstrates his ability to bridge theoretical control methods with real-world industrial applications, reducing risk and improving efficiency in high-stakes environments. While his citation count is still growing, Zhou’s research has immediate relevance to advanced manufacturing, where automation of complex, force-sensitive operations remains a frontier. His approach offers a pathway toward safer, more autonomous robotics in industries handling brittle or deformable materials, marking him as an emerging voice in manipulation planning and learning-based control.
Research Focus
Key Achievements
Top Papers
- 1